Small island nations and developing countries are emerging as unexpected powerhouses in the global race to build AI data centers, competing directly with the United States and China for infrastructure investment. Trinidad and Tobago recently signed its first-ever data center agreements with American tech companies, while Mauritius, Malaysia, and Costa Rica are rapidly positioning themselves as major hubs for artificial intelligence computing. The shift reveals a fundamental truth about modern AI infrastructure: the most important factors aren't proximity to Silicon Valley or cutting-edge tech talent, but rather abundant electricity, reliable internet connectivity, and available land.

What Makes Small Countries Attractive for AI Data Centers?

At first glance, building data centers thousands of miles away from North American tech companies seems illogical. But the economics tell a different story. The key distinction lies in understanding two different types of data centers and their distinct geographic needs.

AI training centers, which build proprietary models like Anthropic's Claude or Google's Gemini, require enormous computing power but can operate almost anywhere geographically. Once an AI model is trained, it can be deployed elsewhere. Inference centers, by contrast, handle everyday user requests to already-trained AI systems, like ChatGPT queries, and must be closer to users because even small delays matter. For training facilities, geography is far less important than access to abundant electricity, land, and internet connectivity to link computers to the rest of the world.

"You run your job, the computer chugs at it until you have your results or your AI model," explained Heather West, a geotechnology expert at Eurasia Group, describing the training process.

Heather West, Geotechnology Expert at Eurasia Group

This distinction is reshaping where companies look to build. In many cases, the cheapest and fastest place to construct a data center isn't the United States, where electricity and labor costs are high, but wherever companies can secure reliable power, enough land, and the internet infrastructure to connect those computers globally.

How Are Specific Countries Positioning Themselves as AI Data Center Hubs?

• Trinidad and Tobago: The Caribbean nation of 1.5 million people signed agreements with American tech companies last month to build its first data centers. The country benefits from natural gas reserves that generate nearly all of its electricity and sits at a crossroads of multiple subsea fiber-optic cables linking North America, South America, and the Caribbean. Government officials project the investment will bring over 5,000 jobs, though critics have questioned whether the nation can sustain the enormous electricity and water demands.
• Mauritius: This island nation off the coast of East Africa, less than half the size of Trinidad and Tobago, already hosts 10 smaller telecom data centers and is investing heavily in increased connectivity with more undersea cables to expand its ability to host larger AI facilities.
• Malaysia: The country has emerged as a major destination for AI data centers in Asia by recycling land once used for palm oil production. It has attracted investments from Microsoft, Google, and Amazon to build their own data centers, some for training AI models and others serving computing needs in neighboring Singapore, where land and power have become increasingly scarce and expensive.
• Costa Rica: The country hopes to capitalize on its green energy credentials by offering companies a significantly lower carbon footprint. Costa Rica generates 98% of its electricity from renewable sources, making it an attractive option for environmentally conscious tech companies.

These countries represent a new economic opportunity similar to how smaller nations once competed to attract banks and offshore finance through favorable tax policies. Now, they're competing for something far more concrete: the physical infrastructure that powers artificial intelligence.

How Are the US and China Competing for Global AI Infrastructure?

The United States has already begun encouraging American companies to expand AI infrastructure overseas through initiatives like the American AI Exports Program, which aims to promote US AI technology hardware, software, and data systems abroad. The strategic thinking is clear: once countries adopt American AI infrastructure, switching to Chinese alternatives becomes politically and technically more difficult.

"Washington hopes that countries building on the American AI stack will become embedded in American tech standards and commercial ecosystems," noted Jessica Brandt, senior fellow for Technology and National Security at the Council on Foreign Relations.

Jessica Brandt, Senior Fellow for Technology and National Security at the Council on Foreign Relations

China is pursuing a parallel strategy through investments across the Global South, financing digital infrastructure that mirrors its broader Belt and Road ambitions. Kenya is hosting Chinese-built data centers and is building a 5,000-acre "technopolis" just outside of Nairobi with Chinese funding. Range IDC, another Chinese firm, committed $5 billion to build its first data center in Batam, Indonesia, marking the company's first expansion outside mainland China. Central Asian countries are also seeking to participate, though limited energy resources and connectivity have constrained Chinese investment so far.

What Are the Risks and Opportunities for Smaller Nations?

The demand for AI data centers, combined with competition between the US and China, presents both significant opportunities and real challenges for smaller countries. A major AI data center can bring billions of dollars in investment, new infrastructure, and closer ties with the world's leading AI companies. However, these facilities consume enormous amounts of electricity and resources to keep running.

For smaller countries like Trinidad and Tobago, the central challenge will be ensuring they become more than just landlords of the machines behind the AI boom. The infrastructure investment is real, but so are the resource demands. Countries must carefully evaluate whether their existing power grids, water systems, and environmental capacity can sustain these facilities long-term while still delivering meaningful economic benefits to their populations beyond job creation announcements.

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